Senior Analytics Engineer

Vancouver, BC · Vancouver · CAD 106,000-120,000 / year · 4+ years experience · Hybrid · Posted Oct 15, 2026

At a glance

Asana is a leading platform for human + AI collaboration. Millions of teams around the world rely on Asana to achieve their most important goals, faster. Asana has been named to Fortune's Best Workplaces for 7+ years and recognized by Fast Company, Forbes, and Gartner for excellence in workplace culture and innovation. We offer an exceptional office-centric culture while adopting the best elements of hybrid models to ensure that every one of our global team members can work together effortlessly. With 13+ offices all over the world, we are always looking for individuals who care about building technology that drives positive change in the world and a culture where everyone feels that they belong.
We believe in supporting people to do their best work and thrive. Our goal is to ensure that Asana upholds an environment where all people feel that they are respected and valued, whether they are applying for an open position or working at the company. We provide equal employment opportunities to all applicants without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by law.
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The Senior Analytics Engineer sits at the intersection of Data Engineering, Analytics, and Data Science to own the data foundations for a business domain.
This role focuses on transforming raw data into reliable, business-ready datasets and defining the business logic and metric standards for AI-powered self-serve analytics.
The position involves managing the Gold layer and semantic layer to support critical product and business decisions.

Design and improve curated, dimensional data models for downstream dashboards and ELT reporting.
Implement canonical business logic for core KPIs into governed, versioned metric marts.
Author metadata, documentation, and metric definitions to power self-serve analytics via Claude and Databricks Genie.
Maintain a metric dictionary as a single source of truth for domain-specific metrics.
Author data contracts and SLAs at the Silver to Gold boundary.
Own data quality, freshness, and on-call responsibilities for Gold and metric-mart failures.
Build and maintain certified, board-ready dashboards on governed Gold data.
Partner with Product, Business, Data Science, and Engineering teams to translate ambiguous questions into scalable datasets.

4+ years in analytics engineering, data engineering, or a closely related analytics role.
Advanced SQL skills and strong data modeling fundamentals including dimensional modeling, star/snowflake schemas, and slowly changing dimensions.
Hands-on experience with a transformation framework like dbt.
Experience with orchestration tooling such as Airflow.
Proficiency with version control using Git.
Experience with modern warehouse/lakehouse platforms.
Practical experience with data quality testing, observability, schema management, and data contracts.
Demonstrated domain fluency in at least one business area such as PLG funnels, SLG pipeline, marketing attribution, or revenue/ARR.
Strong cross-functional partnership skills including requirement gathering and documentation.

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